Model comparison
GPT-4.5 vs Trinity Large Thinking
Trinity Large Thinking is the stronger model overall, scoring 38.1 to 36.9 on the Noometry Index.
Last verified . 16 shared benchmarks.
Arcee AISummary
- They share 16 benchmarks with published results for both. GPT-4.5 scores higher in 4 categories and Trinity Large Thinking in 4 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-4.5 leads 41.8 to 33.8.
- Trinity Large Thinking has downloadable open weights; the other is API-only.
Side by side
| GPT-4.5 | Trinity Large Thinking | |
|---|---|---|
| Provider | OpenAI | Arcee AI |
| Noometry Index | 36.9 | 38.1 |
| Released | 2025-02-27 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | — | 262K |
| Max output | — | 80K |
| Input $ / M tokens | — | $0.25 |
| Output $ / M tokens | — | $0.80 |
| Results tracked | 42 | 24 |
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Category by category
Coding GPT-4.5 leads
GPT-4.5: 41.8 (#102), Trinity Large Thinking: 33.8 (#238)
| Benchmark | GPT-4.5 | Trinity Large Thinking |
|---|---|---|
| LMArena Coding | 1397 | 1381 |
| Aider Polyglot | 44.9% | — |
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |
| WeirdML | 39.4% | — |
| LiveBench Coding | 75.2% | — |
Agentic & Tool Use Not comparable
GPT-4.5: 27.6 (#92), Trinity Large Thinking: —
| Benchmark | GPT-4.5 | Trinity Large Thinking |
|---|---|---|
| Cybench | 17.5% | — |
Reasoning Trinity Large Thinking leads
GPT-4.5: 14.1 (#320), Trinity Large Thinking: 16.3 (#298)
| Benchmark | GPT-4.5 | Trinity Large Thinking |
|---|---|---|
| LMArena Hard Prompts | 1404 | 1350 |
| ARC-AGI-2 | 0.8% | — |
| SimpleBench | 34.5% | — |
| NYT Connections (extended) | — | 16.5% |
| ARC-AGI-1 | 10.3% | — |
| CritPt | — | 0.9% |
| EnigmaEval | 3.2% | — |
| Thematic Generalization | — | 41.6% |
| LiveBench Reasoning | 71.1% | — |
| LiveBench Data Analysis | 64.3% | — |
| Surface Evolver Bench | — | 15.6% |
| Epoch Capabilities Index | 136.74 | — |
| ForecastBench | 61.7 | — |
| LiveBench | 69% | — |
Math Trinity Large Thinking leads
GPT-4.5: 31.0 (#200), Trinity Large Thinking: 34.9 (#149)
| Benchmark | GPT-4.5 | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1412 | 1366 |
| OTIS Mock AIME 2024-2025 | 37.8% | — |
| LiveBench Math | 69.3% | — |
| MATH Level 5 | 78.6% | — |
Knowledge Trinity Large Thinking leads
GPT-4.5: 32.4 (#205), Trinity Large Thinking: 40.3 (#107)
| Benchmark | GPT-4.5 | Trinity Large Thinking |
|---|---|---|
| LMArena Expert | 1394 | 1359 |
| GPQA Diamond | 68.7% | — |
| Humanity's Last Exam | 5.4% | — |
| Confabulations | 13.6% | — |
| Vectara Hallucination Rate | — | 6.9% |
Multimodal Not comparable
GPT-4.5: 37.0 (#68), Trinity Large Thinking: —
| Benchmark | GPT-4.5 | Trinity Large Thinking |
|---|---|---|
| LMArena Vision | 1195 | — |
| VPCT | 45% | — |
Multilingual GPT-4.5 leads
GPT-4.5: 52.7 (#78), Trinity Large Thinking: 46.4 (#155)
| Benchmark | GPT-4.5 | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1413 | 1325 |
| LMArena Chinese | 1421 | 1372 |
| LMArena French | 1417 | 1374 |
| LMArena German | 1457 | 1356 |
| LMArena Japanese | 1416 | 1312 |
| LMArena Korean | 1392 | 1304 |
| LMArena Russian | 1419 | 1338 |
| LMArena Spanish | — | 1356 |
Instruction Following GPT-4.5 leads
GPT-4.5: 72.8 (#129), Trinity Large Thinking: 70.7 (#157)
| Benchmark | GPT-4.5 | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1404 | 1334 |
| LiveBench Instruction Following | 72.3% | — |
Long Context Too close to call
GPT-4.5: 40.4 (#150), Trinity Large Thinking: 41.2 (#139)
| Benchmark | GPT-4.5 | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1406 | 1355 |
| Fiction.LiveBench | 63.9% | — |
Writing & Preference GPT-4.5 leads
GPT-4.5: 57.1 (#129), Trinity Large Thinking: 54.0 (#152)
| Benchmark | GPT-4.5 | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1417 | 1340 |
| LMArena Creative Writing | 1394 | 1321 |
| LMArena Multi-Turn | 1444 | 1342 |
| Short-Story Creative Writing | 75.6% | — |
| EQ-Bench Creative Writing | 1258 | — |
| LiveBench Language | 61.5% | — |
Frequently asked questions
Is GPT-4.5 better than Trinity Large Thinking?
Trinity Large Thinking is the stronger model overall, scoring 38.1 to 36.9 on the Noometry Index.
Is GPT-4.5 or Trinity Large Thinking better for coding?
GPT-4.5 scores higher on coding benchmarks: 41.8 versus 33.8 in the Noometry coding category.
How many benchmarks do GPT-4.5 and Trinity Large Thinking share?
16 benchmarks have published results for both models. GPT-4.5 has 42 scored results on Noometry and Trinity Large Thinking has 24.